Session 1: Data Production, Usage and Integration

Background: Builds political applications so citizens can understand what their government is doing. One of the founders of the open data network in Germany.

- access to or production of structured datasets
- provide raw data dor the users alogn with the story: as a spreadsheet, and/or interactive environment (eg map-mashup with a timeslide and filters). Provide the reader with a research environment.

The Wikileaks Warlogs were a wakeup call for DDJ in Germany.

OpenGov data is a subsection of open data but there is no OpenGov initiative in Germany like data.gov. The data available is not very detailed and not in a machine readable format. OpenData in Germany is happing from bottom-up: several groups and people are working on gathering (scraping) data from government sites and developing applications. There is an evolving ecosystem of citizen apps, eg:
OpenBudget offener-haushalt.de
OpenParliament openbundestag.de
Lobbyregister lobbypedia.de

We can use this ecosystem as weatherstations or seismographs:
Measuring political temperature, pressure, etc.
Journalists could find stories in the data and usage of this application
Newspapers/media should sponsor or develop apps like this for reader/user environment as a watchdog position.
 

Session 1: Data Production, Usage and Integration

From rivalrous goods (print) to non-rivalrous goods (bits).
We need to move beyond datasets used to illustrate reports.

There is an opportunity for an ecosystem of open data:
- small pieces, loosely joined
- easy to reuse, easy to recombine
- lots of contributors/maintainers
- distributed, decentralised
- divide and conquer
- revision, itirative, wiki like

Making the news:
- Finding new stories in datasets
- Bigger picture by linking datsets
- More pairs of eyes to spot patterns
- Harnessing more external expertise
- Analysing data behind the stories
- Responding to interest from public
- Putting stories into context
- Publishing datasets wihh stories
- Create new interfaces to data and stories

Spreading the news:
- Visually representing data
- Demand driven delivery
- Datasets for others to reuse
- Enabling users to comment flag
- Integration with other services
- Connecting data to stories

Data-driven Journalism: What is There to learn?
Organized by the European Journalism Centre

Opening – Mirko Lorenz: Five Ws (and one H)

Premise: data provides a new perspective for journalism.
Where do journalists meet within the new field of data-driven journalism? What is their common ground? Programming journalists versus storytelling journalists.

Data-driven journalism (DDJ) is a workflow, where data is the basis for analysis, visualization and storytelling.

Foggy: Platforms, tools, formats, business models, financing.

Data > filter > visualize > story (value to the public chain)

DDJ as the rescue for the old journalism model of subscriptions and ads that has fallen apart? The future directions of DDJ:
- Reduce time to search
- Minimize need to reformat
- Enable decisions (eg politicians, oil cleaning companies)
- Detect anomolies earlier
- Be trustable

How? DDJ is in search of insights how to structure their material better in platforms like Holovaty/Everyblock. Inspiration: Alexander L. Holley (1832-1882) who had a deep interest in technology, trained as an engineer and writer, and a foreign technical correspondent for the New York Times.